Book Review: An Aesthetic Education in the Era of Globalization, Gayatri C. Spivak
Bibliographic record
Abstract
An Aesthetic Education in the Era of Globalization (AEEG) has 25 essays spanning a period of 23 years and represents Spivak's cumulative retrospection on the meaning, difficulties, joys and paradoxes of teaching in the humanities focusing on the conflictual intersections of ethics, aesthetics and politics. The book has been described as an enthusiastic reminder of “pedagogy’s power to reach beyond the logic of capital” (Bari, 2012, p.1). The book offers a patterned mosaic of her pedagogical propositions, something that can be extremely useful for thinking education “otherwise.” However, in order to give justice to Spivak’s propositions it is necessary to trace them back to the context of critique within which they emerged. Therefore, what I decided to do in this review article is to offer a very brief synthesis of Spivak’s critiques and propositions that I think are of most value to an “Other” education and, in order to do this, I will focus on her work as whole; not only her latest book...
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".